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                    <span class="info-title" contenteditable="true">基本信息</span>
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                        <label class="left-label" contenteditable="true">姓名</label><span class="label-value" contenteditable="true">&nbsp;&nbsp;颜剑锋</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span>
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                        <label class="left-label" contenteditable="true">专业</label><span class="label-value" contenteditable="true">&nbsp;&nbsp;计算机软件与理论</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span>
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                        <label class="left-label" contenteditable="true">教育</label><span class="label-value" contenteditable="true">&nbsp;&nbsp;硕士</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span>
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                        <label class="left-label" contenteditable="true">学校</label><span class="label-value" contenteditable="true">&nbsp;&nbsp;北京大学</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span>
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                        <label class="left-label" contenteditable="true">学院</label><span class="label-value" contenteditable="true">&nbsp;&nbsp;信息科学技术学院</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span>
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                        <label class="left-label" contenteditable="true">毕业时间</label><span class="label-value" contenteditable="true">&nbsp;&nbsp;2019.07</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span>
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                <h2 class="info-header"><i class="iconfont icon-call"></i> <span class="info-title" contenteditable="true">联系方式</span><span class="item-add" style="visibility: hidden;"><i class="iconfont icon-playlistadd"></i></span><span class="unit-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span></h2>
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                        <label class="left-label" contenteditable="true">手机</label><span class="label-value" contenteditable="true">+86&nbsp;&nbsp;18810580622</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span></li>
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                <h2 class="info-header"><i class="iconfont icon-star"></i> <span class="info-title" contenteditable="true">语言与技能</span><span class="item-add" style="visibility: hidden;"><i class="iconfont icon-playlistadd"></i></span><span class="unit-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span></h2>
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                <h2 class="info-header"><i class="iconfont icon-project"></i> <span class="info-title" contenteditable="true">学术成果</span>
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                        <label class="left-label" contenteditable="true">2020</label>
                        <span class="label-value" contenteditable="true">Dense Hybrid Recurrent Multi-view Stereo Net with Dynamic Consistency Checking (<strong>ECCV2020</strong>)</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span></li>
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                <h2 class="info-header"><i class="iconfont icon-education"></i> <span class="info-title" contenteditable="true">教育背景</span></h2>
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                        <label class="left-label" contenteditable="true">2016~2019</label><span class="label-value" contenteditable="true">北京大学, 计算机软件与理论, 硕士</span>
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                        <label class="left-label" contenteditable="true">2011~2015</label><span class="label-value" contenteditable="true">福建师范大学, 软件工程, 学士</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span>
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                        <label class="left-label" contenteditable="true">2018</label><span class="label-value" contenteditable="true">北京大学诗歌朗诵会 摄影师</span><span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span></li>
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                       <label class="left-label" contenteditable="true">2017</label><span class="label-value" contenteditable="true">北京大学中乐学社与圣母大学手铃乐团联合音乐会 组织者</span> <span class="item-remove" style="visibility: hidden;"><i class="iconfont icon-delete"></i></span></li>
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                <h2 class="info-header"><i class="iconfont icon-project"></i> <span class="info-title" contenteditable="true">工作经验</span>
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                        <h3 contenteditable="true">工作时间:2020.09~至今&nbsp;&nbsp;工作地点:百度&nbsp;&nbsp;职位:高级研发工程师<br/></h3>
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                                    <strong style="">工作内容一: 人脸融合</strong><br/>
                                    <strong>简要介绍: </strong>通过快速精准地定位人脸关键点,将用户上传的照片与特定形象进行面部层面融合,使生成的图片同时具备用户与特定形象的外貌特征<br/>
                                    <strong>创新一: </strong>实现可变脸型效果，即保持用户图的脸型特征 <br/>
                                    <strong>创新二: </strong>实现保留模板图表情效果 <br/>
                                    <strong>创新三: </strong>实现大侧脸换脸稳定性和时序稳定性 <br/>
                                    <strong>创新四: </strong>以GPEN作为GANPrior， 实现换脸功能，换脸效果更加清晰，更加美观。<br/>
                                    <strong>创新五: </strong> 多级流水线设计，实现云上一倍速实时换脸。将视频分段，异步融合，可进一步提升速度。
                                    <strong>经验: </strong>作为人脸融合技术负责人，负责算法优化、工程实现、落地上线等全流程工作。<br/>
                                    <strong>收益：</strong>应用落地到央视、人民日报、新华社、南方财经、深圳地铁等标杆企业。图片人脸融合日均pv 30万。作为换脸服务供应商，上线ios app： 换颜。<br/>
                                
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                                    <strong>工作内容二: 表情驱动</strong><br/>
                                    <strong>简要介绍: </strong>基于开源代码first order motion，提升侧脸驱动效果。<br/>
                                    <strong>创新一:</strong> 原论文通过对人脸进行裁剪缩放，我们通过与标准脸关键点对齐，将图片对齐到标准脸上，然后再做人脸驱动。<br/>
                                    <strong>创新二:</strong> 多人脸驱动加速。<br/>
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                        <h3 contenteditable="true">工作时间:2019.07~2020.06&nbsp;&nbsp;工作地点:BIGO&nbsp;&nbsp;职位:视觉算法工程师<br/></h3>
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                                    <strong >工作内容一: 五官增强</strong><br/>
                                    <strong>简要介绍: </strong>使用rolling guidance 提取图片细节;使用人脸检测网络获取人脸位置;使用人脸分割网络提取人脸五官mask;根据mask对图片进行增强<br/>
                                    <strong>创新一: </strong>根据rolling guidance 的迭代特性，取其中两次滤波结果相减得到细节，达到去除噪声的同时，保留细节。<br/>
                                    <strong>创新二: </strong>使用bit位操作进行权值计算，大大加快了滤波速度，在arm7机型上，640x360的图片，只需要3.5ms，满足大部分移动设备的实时性需求。<br>
                                    <strong>经验: </strong>Neon 代码优化、实现cuda 程序开发、深度学习网络模型的C++接入<br/>
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                                    <strong>工作内容二: GAN网络实现视频画质增强</strong><br/>
                                    <strong>简要介绍: </strong>基于GAN网络，提升视频画质，同时避免出现偏色、渗色、引入artifacts等问题。
                                    <br/>
                                    <strong>创新: </strong>改进参差网络结构和损失计算方式，解决原网络的色偏、渗色等问题。增加后处理，避免出现artifact<br/>
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                <h2 class="info-header"><i class="iconfont icon-project"></i> <span class="info-title" contenteditable="true">项目经历</span>
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                        <h3 contenteditable="true">时间:2018.04~2019.07 项目:基于深度学习的多视图深度计算</h3>
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                            <strong>简要介绍: </strong>通过深度学习的方法预测图片深度，最后得到稠密的点云。主要流程包括:图片特征提取、计算cost volume (已知图片深度、相机参数，通过平面单应对齐相邻帧信息)、估计像素所在深度层的概率。<br/>
                            <strong> 创新一: </strong> 通过SNet网络学习图片像素特征，与UNet相比，具有更快的速度，更少的网络参数。 <br/>
                            <strong> 创新二: </strong>　使用U-LSTM模块，提取三维空间的信息。即将UNet 和　lstm 整合，实现多尺度循环神经网络，提取三维空间信息。<br/>
                            <strong>效果: </strong>在<a href="https://www.tanksandtemples.org">Tanks and Temples </a>评测网站上，至 ECCV2020 投稿截止日2020/03/05，我们超过了目前已有的三维重建方法，<strong>位列第一</strong>。<br/>

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                       <h3 contenteditable="true">时间:2017.09~2018.04 项目:基于分布式的快速点云重建 </h3>
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                           <strong>简要介绍: </strong>传统的方法主要局限于单机单核三维重建，速度较慢。这里主要使用多核并行和多机分布式并行技术加快三维重建速度。<br/>
                           <strong>创新:</strong> 实现线程池，实现对若干块子点云拼接成完整点云。<br/>
                           <strong>方法: </strong>openmp,mpich,线程池
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